Data quality analysis method and system, terminal and readable storage medium

Abstract

The invention discloses a data quality analysis method and system, a terminal and a readable storage medium, and the method comprises the steps: obtaining a data quality detection rule of a database, screening preset data quality rules according to the data quality detection rule, and obtaining a target data quality rule; the method comprises the steps of obtaining business data input into a database by a user, dividing the business data according to a preset quality detection plan to obtain a target planning set, and verifying the target planning set according to a target data quality rule to obtain a detection result; and analyzing the detection result according to a preset alarm rule, generating service data quality alarm information, analyzing the service data alarm information, and generating a data quality monitoring analysis report. According to the method, the data quality condition in the monitoring database is analyzed through rule screening, data division, verification and alarm analysis, the quality monitoring analysis report is generated, the data analysis accuracy is improved, and the data quality is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data quality analysis method, system, terminal and computer-readable storage medium. Background Art

[0002] At present, in the existing technology, the analysis of data quality problems includes but is not limited to information reasons, process reasons, technical reasons and personnel reasons: information reasons refer to abnormal data norms, including data standard abnormalities, data quality rule abnormalities, change frequency abnormalities, etc.; process reasons refer to improper settings of information system processing procedures and manual operation procedures, including data creation, transmission, loading, use, maintenance and auditing processes; technical reasons refer to abnormalities in various technical links of data processing, including improper design of data verification rules, improper data source access, limited data storage capacity, etc., mainly involving data creation, data acquisition, data transmission, data loading, data use, data maintenance and other links; personnel reasons refer to insufficient personnel and management mechanisms, including lack of personnel training, unclear data responsible persons, insufficient incentive and feedback mechanisms, etc. However, in the existing process of analyzing data quality problems, monitoring and analysis tools are used, and the result data generated by the monitoring and analysis tools is realized in the form of reports, which makes the data readability poor, and the early warning thresholds set manually will reduce the accuracy and timeliness of data early warnings, thereby reducing the accuracy of data quality.

[0003] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0004] The main purpose of the present invention is to provide a data quality analysis method, system and computer-readable storage medium, aiming to solve the problems of poor data reporting quality and low accuracy of data quality analysis results when analyzing data in the prior art.

[0005] To achieve the above object, the present invention provides a data quality analysis method, which comprises the following steps:

[0006] Acquire data quality detection rules of the database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules;

[0007] Obtaining business data input into the database by the user, dividing the business data according to a preset quality inspection plan to obtain a target planning set, verifying the target planning set according to the target data quality rule, and obtaining a inspection result;

[0008] The detection result is parsed according to preset alarm rules to generate business data quality alarm information, the business data alarm information is analyzed to generate a data quality monitoring and analysis report.

[0009] Optionally, the acquiring of business data input into a database by a user, dividing the business data according to a preset quality inspection plan to obtain a target planning set, and verifying the target planning set according to a target data quality rule to obtain a inspection result specifically includes:

[0010] Obtaining business data input into a database by a user, dividing the business data according to a preset quality inspection plan to obtain a plurality of planning sets, and screening the plurality of planning sets according to a preset scoring level to obtain a target planning set;

[0011] Verifying the target planning set according to the target data quality rule to obtain verified business data and rule verification information;

[0012] Determine the data description indicator status according to the verified business data and the rule verification information;

[0013] The detection result is generated based on the verified business data, the rule verification information and the data description indicator status.

[0014] Optionally, the data quality analysis method, wherein the business data input into the database by the user is obtained, the business data is divided according to a preset quality detection plan to obtain a target planning set, and the target planning set is verified according to a target data quality rule to obtain a detection result, and then further includes:

[0015] An evaluation report is generated according to the rule verification information and the detection results, and the current user is prompted to correct unqualified data in the evaluation report.

[0016] Optionally, the data quality analysis method, wherein generating an evaluation report according to the rule verification information and the test results, and prompting the current user to correct unqualified data in the evaluation report, specifically includes:

[0017] Scoring the business data according to the rule verification information and the detection result;

[0018] Determine the quality problem of the business data according to the score, and output the score and the quality problem to the evaluation report;

[0019] According to the evaluation report, the current user is prompted to correct the unqualified data in the evaluation report.

[0020] Optionally, the data quality analysis method, wherein the detection result is parsed according to a preset alarm rule to generate business data quality alarm information, the business data alarm information is analyzed to generate a data quality monitoring and analysis report, further comprises:

[0021] Obtain the indicators of business data for configuration and obtain the indicator configuration table;

[0022] The indicator configuration information in the indicator configuration table and the detection result are calculated to obtain an indicator value, and an indicator data quality report is generated based on the change data of the indicator value within a preset time range.

[0023] Optionally, the data quality analysis method, wherein the detection result is parsed according to a preset alarm rule to generate business data quality alarm information, the business data alarm information is analyzed to generate a data quality monitoring and analysis report, specifically includes:

[0024] Analyze the detection result according to the preset alarm rules to generate the service data quality alarm information;

[0025] Extracting characteristic information from the service data quality warning information to obtain service result characteristic information;

[0026] Performing a fusion analysis on the business data and the business result characteristic information to obtain an analysis result of the business data;

[0027] If the analysis results meet the alarm conditions, a data quality monitoring and analysis report is generated.

[0028] Optionally, the data quality analysis method further comprises:

[0029] Constructing a metadata analysis model according to the evaluation report;

[0030] The path nodes of the business data are located according to the metadata analysis model, the path nodes are associated with the business data, and a plurality of associated data tables are established.

[0031] In addition, to achieve the above-mentioned purpose, the present invention further provides a data quality analysis system, wherein the data quality analysis system:

[0032] A data quality rule screening module is used to obtain data quality detection rules of the database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules;

[0033] A business data verification module is used to obtain business data input by a user into a database, divide the business data according to a preset quality inspection plan, obtain a target planning set, and verify the target planning set according to the target data quality rule to obtain a detection result;

[0034] The analysis report generation module is used to parse the detection results according to preset alarm rules, generate business data quality alarm information, analyze the business data alarm information, and generate a data quality monitoring analysis report.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a data quality analysis program, and when the data quality analysis program is executed by a processor, the steps of the data quality analysis method as described above are implemented.

[0036] In the present invention, the data quality detection rules of the database are obtained, and the preset data quality rules are screened according to the data quality detection rules to obtain the target data quality rules; the business data input into the database by the user is obtained, and the business data is divided according to the preset quality detection plan to obtain the target planning set, and the target planning set is verified according to the target data quality rules to obtain the detection results; the detection results are parsed according to the preset alarm rules to generate business data quality alarm information, and the business data alarm information is analyzed to generate a data quality monitoring and analysis report. The present invention uses rule screening, data division, verification, alarm parsing, and analysis to monitor the data quality in the database, generate a quality monitoring and analysis report, improve data analysis accuracy, and improve data quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of a preferred embodiment of the data quality analysis method of the present invention;

[0038] Figure 2 is a flow chart of the data quality management scope in a preferred embodiment of the data quality analysis system of the present invention;

[0039] Figure 3 is a flow chart of data quality control in a preferred embodiment of the data quality analysis system of the present invention;

[0040] Figure 4 It is a flow chart of in-process control and monitoring of data quality in a preferred embodiment of the data quality analysis system of the present invention;

[0041] Figure 5 It is a structural diagram of a preferred embodiment of the data quality analysis system of the present invention;

[0042] Figure 6It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] In the prior art, monitoring and analysis tools are used in the process of analyzing data quality problems. The result data generated by the monitoring and analysis tools is realized in the form of reports, which makes the data readability poor. In addition, the warning thresholds set manually will reduce the accuracy and timeliness of data warnings. Therefore, a data quality analysis method is needed, which can improve the accuracy of data analysis through data models to supervise and improve data quality.

[0045] The data quality analysis method described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the data quality analysis method comprises the following steps:

[0046] Step S10: Acquire data quality detection rules of the database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules.

[0047] Specifically, the data quality detection rules of the database are obtained, and the preset data quality rules are screened according to the data quality detection rules (the data quality detection rules include the inspection of quality rules and the exploration of source systems. The data quality rule inspection should check the rationality of data business rules, verify the consistency of cross-system data, etc.), and obtain the target data quality rules.

[0048] As an example, there are three data quality detection rules, namely timeliness data quality detection rule, consistency data quality detection rule and integrity data quality detection rule; among them, the timeliness data quality detection rule detects the time interval from the generation to the viewing of the preset data quality rule. If the time interval is less than the preset value, the target data quality rule is judged to be passed; if the time interval is not less than the preset value, the target data quality rule is judged to be failed; the consistency data quality detection rule is to check whether the same data from different data sources are consistent at the same time point. If they are consistent, the target data quality rule is judged to be passed; if they are inconsistent, the target data quality rule is judged to be failed; the integrity data quality detection rule is to check whether the corresponding data in the database is empty data. If the corresponding data is not empty data, the target data quality rule is judged to be passed; if the corresponding data is empty data, the target data quality rule is judged to be failed.

[0049] Furthermore, if Figure 2 As shown in the figure, by improving the data value, we formulate data quality rules, use IT tools to control data quality, improve data quality, and finally get the effect of improving data value. According to the effect of improving data value, we can meet the demand for improving data value, such as Figure 3 As shown, by checking the preset data quality rules in advance, the data quality can be checked before going online, and then the data is audited through the preset data quality rules to determine the data that does not meet the quality standards. The data with quality problems is directly terminated, and finally the data problems are located and analyzed to obtain a data quality analysis report.

[0050] Step S20, obtaining the business data input into the database by the user, dividing the business data according to a preset quality inspection plan to obtain a target planning set, verifying the target planning set according to the target data quality rule to obtain a inspection result.

[0051] Specifically, Figure 4 As shown, the business data input by the user into the database is obtained, the business data is divided according to a preset quality inspection plan to obtain multiple planning sets, the multiple planning sets are screened according to a preset scoring level (the business data is extracted according to a preset neural network to obtain business feature data, the business feature data is weighted analyzed to obtain a scoring level of the business data, and the multiple planning sets are sorted according to the scoring level) to obtain a target planning set; the target planning set is verified according to the target data quality rule (when the user enters the business data, the system first needs to verify the target planning set to ensure that there is no formal error in the target planning set and improve the data quality), and the verified business data and rule verification information are obtained; according to the verified business data and The rule verification information determines the state of the data description indicator (for example, if the customer name in the user's order information is filled in incorrectly, after the incorrect customer name is modified, the accuracy of the data may be determined based on the modified customer name. If the customer name is blank, the user needs to be prompted that the customer name is missing, and it can be determined that there is a problem with the integrity of the data; at the same time, it is also necessary to output the test result according to the rule verification information, which can prompt the user that the incorrect order information has been modified to avoid errors caused by the system automatically modifying certain special formats of order information. Without affecting the personalization of the user-entered order information, input errors are avoided to the greatest extent, effectively improving data quality); the test result is generated based on the verified business data, the rule verification information and the data description indicator state.

[0052] Furthermore, an evaluation report is generated based on the rule verification information and the detection results, and the current user is prompted to correct unqualified data in the evaluation report; a metadata analysis model is constructed based on the evaluation report; the path nodes of the business data are located according to the metadata analysis model, the path nodes and the business data are associated, and multiple associated data tables are established (the metadata lineage analysis function locates problem data path nodes and associated data).

[0053] As an example, the business data is scored according to the rule verification information and the detection results; quality issues of the business data are determined according to the score, and the score and the quality issues are output to the evaluation report (all unqualified aspects of the data input by the current user are displayed in the evaluation report to prompt the user to modify the data); and the current user is prompted to correct the unqualified data in the evaluation report according to the evaluation report.

[0054] Step S30: parse the detection result according to preset alarm rules to generate business data quality alarm information, analyze the business data alarm information, and generate a data quality monitoring and analysis report.

[0055] Specifically, the indicators of the business data are obtained and configured to obtain an indicator configuration table; the indicator configuration information in the indicator configuration table and the detection result are calculated to obtain the indicator value (the indicators of the business data are obtained and configured, the indicator configuration information in the indicator configuration table is parsed, the indicator operation mode is obtained, and it is determined whether there is an indicator to be calculated in the indicator configuration table, if so, the indicator operation mode matching the indicator to be calculated is determined, and according to the indicator operation mode matching the indicator to be calculated, the detection results are summarized and calculated to obtain the indicator value), and according to the change data of the indicator value within a preset time range, an indicator data quality report is generated; the detection result is parsed according to the preset alarm rule to generate the business data quality alarm information; Feature information is extracted from the business data quality alarm information to obtain business result feature information; the business data and the business result feature information are integrated and analyzed to obtain analysis results of the business data (the business data and the business result feature information are integrated and analyzed to obtain time series features of the business data; a time series feature label matrix is ​​constructed according to the time series features of the business data, and cluster centers are calculated for the time series feature label matrix to obtain variance values ​​corresponding to the time series feature label matrix; based on the variance values ​​corresponding to the time series feature label matrix and a preset standard variance value, the time series feature label matrix is ​​analyzed to obtain analysis results corresponding to the time series feature label matrix); if the analysis results meet the alarm conditions, a data quality monitoring analysis report is generated.

[0056] Furthermore, if Figure 5 As shown, based on the above data quality analysis method, the present invention also provides a data quality analysis system, wherein the data quality analysis system includes:

[0057] A data quality rule screening module 51 is used to obtain data quality detection rules of a database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules;

[0058] The business data verification module 52 is used to obtain the business data input into the database by the user, divide the business data according to the preset quality inspection plan, obtain the target planning set, and verify the target planning set according to the target data quality rule to obtain the inspection result;

[0059] The analysis report generating module 53 is used to analyze the detection result according to the preset alarm rules, generate business data quality alarm information, analyze the business data alarm information, and generate a data quality monitoring analysis report.

[0060] Furthermore, if Figure 6 As shown, based on the above data quality analysis method and system, the present invention also provides a terminal, which includes a processor 10, a memory 20 and a display 30. Figure 6 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0061] The memory 20 may be an internal storage unit of the terminal in some embodiments, such as a hard disk or memory of the terminal. The memory 20 may also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Furthermore, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal, etc. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a data quality analysis program 40 is stored on the memory 20, and the data quality analysis program 40 can be executed by the processor 10, thereby realizing the data quality analysis method in the present application.

[0062] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code stored in the memory 20 or process data, such as executing the data quality analysis method.

[0063] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components of the terminal communicate with each other via a system bus.

[0064] In one embodiment, when the processor 10 executes the data quality analysis program 40 in the memory 20, the following steps are implemented:

[0065] Acquire data quality detection rules of the database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules;

[0066] Obtaining business data input into the database by the user, dividing the business data according to a preset quality inspection plan to obtain a target planning set, verifying the target planning set according to the target data quality rule, and obtaining a inspection result;

[0067] The detection result is parsed according to preset alarm rules to generate business data quality alarm information, the business data alarm information is analyzed to generate a data quality monitoring and analysis report.

[0068] The acquiring of the business data input by the user into the database, dividing the business data according to a preset quality inspection plan to obtain a target planning set, and verifying the target planning set according to a target data quality rule to obtain a inspection result specifically includes:

[0069] Obtaining business data input into a database by a user, dividing the business data according to a preset quality inspection plan to obtain a plurality of planning sets, and screening the plurality of planning sets according to a preset scoring level to obtain a target planning set;

[0070] Verifying the target planning set according to the target data quality rule to obtain verified business data and rule verification information;

[0071] Determine the data description indicator status according to the verified business data and the rule verification information;

[0072] The detection result is generated based on the verified business data, the rule verification information and the data description indicator status.

[0073] The process of obtaining the business data inputted by the user into the database, dividing the business data according to a preset quality inspection plan to obtain a target planning set, and verifying the target planning set according to a target data quality rule to obtain a inspection result further includes:

[0074] An evaluation report is generated according to the rule verification information and the detection results, and the current user is prompted to correct unqualified data in the evaluation report.

[0075] The step of generating an evaluation report according to the rule verification information and the test results, and prompting the current user to correct unqualified data in the evaluation report, specifically includes:

[0076] Scoring the business data according to the rule verification information and the detection result;

[0077] Determine the quality problem of the business data according to the score, and output the score and the quality problem to the evaluation report;

[0078] According to the evaluation report, the current user is prompted to correct the unqualified data in the evaluation report.

[0079] The process of parsing the detection result according to the preset alarm rule to generate business data quality alarm information, analyzing the business data alarm information to generate a data quality monitoring and analysis report, further includes:

[0080] Obtain the indicators of business data for configuration and obtain the indicator configuration table;

[0081] The indicator configuration information in the indicator configuration table and the detection result are calculated to obtain an indicator value, and an indicator data quality report is generated based on the change data of the indicator value within a preset time range.

[0082] The analysis of the detection results according to the preset alarm rules to generate business data quality alarm information, the analysis of the business data alarm information to generate a data quality monitoring and analysis report specifically includes:

[0083] Analyze the detection result according to the preset alarm rules to generate the service data quality alarm information;

[0084] Extracting characteristic information from the service data quality warning information to obtain service result characteristic information;

[0085] Performing a fusion analysis on the business data and the business result characteristic information to obtain an analysis result of the business data;

[0086] If the analysis results meet the alarm conditions, a data quality monitoring and analysis report is generated;

[0087] Wherein, the data quality analysis method further includes:

[0088] Constructing a metadata analysis model according to the evaluation report;

[0089] The path nodes of the business data are located according to the metadata analysis model, the path nodes are associated with the business data, and a plurality of associated data tables are established.

[0090] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a data quality analysis program, and when the data quality analysis program is executed by a processor, the steps of the data quality analysis method described above are implemented.

[0091] In summary, the present invention provides a data quality analysis method, system and computer-readable storage medium, the method comprising: obtaining data quality detection rules of a database, screening preset data quality rules according to the data quality detection rules, and obtaining target data quality rules; obtaining business data input into the database by a user, dividing the business data according to a preset quality detection plan, obtaining a target planning set, verifying the target planning set according to the target data quality rules, and obtaining a detection result; parsing the detection result according to a preset alarm rule, generating business data quality alarm information, analyzing the business data alarm information, and generating a data quality monitoring and analysis report. The present invention uses rule screening, data division, verification, alarm parsing, and analysis to monitor the data quality in the database, generate a quality monitoring and analysis report, improve data analysis accuracy, and improve data quality.

[0092] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or terminal system including the element.

[0093] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0094] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A data quality analysis method, characterized in that: The data quality analysis method comprises: Acquire data quality detection rules of the database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules; Obtaining business data input into the database by the user, dividing the business data according to a preset quality inspection plan to obtain a target planning set, verifying the target planning set according to the target data quality rule, and obtaining a inspection result; The detection result is parsed according to preset alarm rules to generate business data quality alarm information, the business data alarm information is analyzed to generate a data quality monitoring and analysis report.

2. The data quality analysis method according to claim 1, characterized in that: The obtaining of the business data input into the database by the user, dividing the business data according to a preset quality inspection plan to obtain a target planning set, and verifying the target planning set according to a target data quality rule to obtain a inspection result specifically includes: Obtaining business data input into a database by a user, dividing the business data according to a preset quality inspection plan to obtain a plurality of planning sets, and screening the plurality of planning sets according to a preset scoring level to obtain a target planning set; Verifying the target planning set according to the target data quality rule to obtain verified business data and rule verification information; Determine the data description indicator status according to the verified business data and the rule verification information; The detection result is generated based on the verified business data, the rule verification information and the data description indicator status.

3. The data quality analysis method according to claim 2, characterized in that: The process of obtaining the business data inputted by the user into the database, dividing the business data according to a preset quality inspection plan to obtain a target planning set, and verifying the target planning set according to a target data quality rule to obtain a inspection result further includes: An evaluation report is generated according to the rule verification information and the detection results, and the current user is prompted to correct unqualified data in the evaluation report.

4. The data quality analysis method according to claim 3, characterized in that: The generating of the evaluation report according to the rule verification information and the test result, and prompting the current user to correct the unqualified data in the evaluation report, specifically includes: Scoring the business data according to the rule verification information and the detection result; Determine the quality problem of the business data according to the score, and output the score and the quality problem to the evaluation report; According to the evaluation report, the current user is prompted to correct the unqualified data in the evaluation report.

5. The data quality analysis method according to claim 1, characterized in that: The detecting result is parsed according to the preset alarm rule to generate the service data quality alarm information, the service data alarm information is analyzed to generate the data quality monitoring and analysis report, and the like is also included: Obtain the indicators of business data for configuration and obtain the indicator configuration table; The indicator configuration information in the indicator configuration table and the detection result are calculated to obtain an indicator value, and an indicator data quality report is generated based on the change data of the indicator value within a preset time range.

6. The data quality analysis method according to claim 1, characterized in that: The analyzing the detection result according to the preset alarm rule to generate the service data quality alarm information, analyzing the service data alarm information to generate the data quality monitoring and analysis report specifically includes: Analyze the detection result according to the preset alarm rules to generate the service data quality alarm information; Extracting characteristic information from the service data quality warning information to obtain service result characteristic information; Performing a fusion analysis on the business data and the business result characteristic information to obtain an analysis result of the business data; If the analysis results meet the alarm conditions, a data quality monitoring and analysis report is generated.

7. The data quality analysis method according to claim 3, characterized in that: The data quality analysis method further comprises: Constructing a metadata analysis model according to the evaluation report; The path nodes of the business data are located according to the metadata analysis model, the path nodes are associated with the business data, and a plurality of associated data tables are established.

8. A data quality analysis system, characterized in that: The data quality analysis system comprises: A data quality rule screening module is used to obtain data quality detection rules of the database, and screen preset data quality rules according to the data quality detection rules to obtain target data quality rules; A business data verification module is used to obtain business data input by a user into a database, divide the business data according to a preset quality inspection plan, obtain a target planning set, and verify the target planning set according to the target data quality rule to obtain a detection result; The analysis report generation module is used to parse the detection results according to preset alarm rules, generate business data quality alarm information, analyze the business data alarm information, and generate a data quality monitoring analysis report.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a data quality analysis program stored in the memory and executable on the processor. When the data quality analysis program is executed by the processor, the steps of the data quality analysis method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data quality analysis program, and when the data quality analysis program is executed by a processor, the steps of the data quality analysis method according to any one of claims 1 to 7 are implemented.

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